Effects of regular use of scalable, technology enhanced solution for primary mathematics education

Mathematics is one of the key subjects in any school curriculum and most teachers agree that mathematical skills are important for students to master. There is an abundance of research in learning mathematics and a consensus exists among researchers that technology can enhance the learning process. However, many factors need to be taken into consideration when introducing technology into teaching mathematics. Developing a more natural collaboration between learning technology experts, teachers, and students ensures all stakeholders are considered. Involving teachers early on helps develop enduring commitment to innovations and practical solutions. Moreover, creating a culture of collaboration between experts in the field and teachers brings to bear the best of what both worlds have to offer. This thesis synthesizes six papers and offers additional findings that focus on how technology experts can collaborate with elementary teachers to improve student learning outcomes. We focus on managing educational change in ways that improve the sustainability of innovations. We also explore how technical and teaching experts co-create effective lesson plans. In one of the six papers we collected and reported teachers’ responses to survey questions covering typical usage patterns on a platform. Teachers’ direct feedback was collected and incorporated to improve technical solutions. Moreover, one study was conducted abroad to measure the effect of culture on the teaching and learning process. Evidence of effectiveness of technologically enhanced lessons and corresponding homework was based on multiple studies in grades 1 - 3, covering 379 students. The effectiveness of educational technology was measured based on two variables: student performance in mathematics, based on the learning objectives specified in the curriculum, and arithmetic fluency measured by how rapidly and accurately students solved basic arithmetic operations. Statistically significant findings show that educational technology can improve two target variables when comparing students who did not use educational technology to students who did. An additional effect size analysis was conducted to verify and compare results with previous research. Based on these results, platform use produced the same or better effect than previous studies. Based on teacher feedback and user growth on the platform, we managed to integrate technology into the regular school classroom in meaningful and sustainable ways. We were clearly able to support teachers in their practice in a manner that resulted in noticeable student achievement gains. A survey revealed a need to emphasize new features that were introduced to the platform in teacher training programs. Teachers also reported having a positive attitude towards the platform and the initiative gained wide acceptance among their peers.Matematiikka on yksi tärkeimmistä kouluaineista pelkästään tuntimääräisesti mitattunakin. Matematiikan osaamista ja oppimista pidetään yleisesti tärkeänä ja arvostettuna taitona. Matematiikan oppimisesta on valtavasti tutkimusta ja tutkijoiden keskuudessa vallitsee yhteisymmärrys tietotekniikan positiivisista mahdollisuuksista edistää matematiikan oppimista. Tietotekniikan ja oppimisen vuorovaikutus on kuitenkin monisyinen vyyhti ja sen onnistunut hyödyntäminen vaatii tutkijoiden, opettajien ja oppilaiden välistä tiivistä ja vuorovaikutteista yhteistyötä. Uusien innovaatioiden ja kokeilujen onnistumiselle ja niihin sitoutumiselle luodaan vahva pohja, kun opettajat otetaan mukaan kehitystyöhön ensimetreiltä lähtien. Tällaisen tiiviin yhteistyökulttuurin vaaliminen mahdollistaa käytännön työn ja teorian vahvuuksien hyödyntämisen. Tämä väitöstyö koostuu kuudesta artikkelista. Artikkelit kuvaavat, kuinka tutkijat ja opettajat työskentelivät yhdessä parantaakseen oppilaiden matematiikan oppimista. Tavoitteenamme oli muuttaa koulun käytänteitä pitkäjänteisesti ja kestävällä tavalla. Tutkimme kuinka tutkijat ja opettajat pystyivät yhdessä luomaan onnistuneita ja tehokkaita oppimiskokonaisuuksia. Opettajat olivat koko ajan kehitystyön keskiössä. Yhdessä kuudesta artikkelista tutkittiin kyselytutkimuksen avulla opettajien kokemuksia ja käyttötottumuksia. Näitä vastauksia hyödynnettiin teknisessä kehitystyössä ja hyvien käytänteiden hiomisessa. Yksi väitöskirjan tutkimuksista tehtiin ulkomailla opetus- ja oppimiskulttuureista vaikutusten huomioimiseksi. Sähköisten oppituntien ja kotitehtävien vaikuttavuuden arviointi perustuu useisiin 1.-3. luokilla tehtyihin tutkimuksiin ja kaikkiaan 379 oppilaan vastauksiin. Sähköisten oppituntien vaikuttavuutta arvioitiin kahden eri mittarin perusteella. Ensin matematiikan taitojen perusteella, eli kuinka hyvin kunkin luokka-asteen oppimistavoitteet olivat täyttyneet ja myöhemmin myös laskusujuvuuden perusteella, eli kuinka nopeasti ja tarkasti oppilaat pystyivät laskemaan peruslaskutoimituksia. Tulokset osoittavat, että opetusteknologian avulla pystytään parantamaan oppilaiden suoriutumista edellä mainittujen osa-alueiden osalta verrattuna oppilaisiin, jotka eivät käyttäneet opetusteknologiaa. Tulokset olivat tilastollisesti merkitseviä. Näiden tulosten varmistamiseksi laskettiin vaikuttavuuden suuruus ja sitä verrattiin aiempiin alan tutkimuksiin. Tulosten perusteella sähköisillä oppitunneilla oli sama tai parempi vaikuttavuus kuin aiemmissa tutkimuksissa. Opettajien palautteiden ja kasvavan käyttäjämäärän perusteella voidaan sanoa, että onnistuimme tavoitteessamme integroida opetusteknologiaa mielekkäällä tavalla osaksi koulutyötä. Onnistuimme myös tukemaan ja auttamaan opettajia opetustyössään ja samalla merkittävästi parantamaan oppilaiden suoriutumista. Kyselytutkimuksen perusteella huomasimme, että uusien ominaisuuksien kouluttamiseen tulee kiinnittää enemmän huomiota. Samassa tutkimuksessa opettajat raportoivat olevansa tyytyväisiä alustaan ja sähköiset oppitunnit näyttävät saaneen vankan jalansijan suomalaisessa opettajakunnassa

Endemic uncertainties : teachers\u27 professional lives in the high-stakes reform movement

Explores the effects that principles of certainty have on teachers\u27 professional lives and their attitudes toward their work

Cognitive Decay And Memory Recall During Long Duration Spaceflight

This dissertation aims to advance the efficacy of Long-Duration Space Flight (LDSF) pre-flight and in-flight training programs, acknowledging existing knowledge gaps in NASA\u27s methodologies. The research\u27s objective is to optimize the cognitive workload of LDSF crew members, enhance their neurocognitive functionality, and provide more meaningful work experiences, particularly for Mars missions.The study addresses identified shortcomings in current training and learning strategies and simulation-based training systems, focusing on areas requiring quantitative measures for astronaut proficiency and training effectiveness assessment. The project centers on understanding cognitive decay and memory loss under LDSF-related stressors, seeking to establish when such cognitive decline exceeds acceptable performance levels throughout mission phases. The research acknowledges the limitations of creating a near-orbit environment due to resource constraints and the need to develop engaging tasks for test subjects. Nevertheless, it underscores the potential impact on future space mission training and other high-risk professions. The study further explores astronaut training complexities, the challenges encountered in LDSF missions, and the cognitive processes involved in such demanding environments. The research employs various cognitive and memory testing events, integrating neuroimaging techniques to understand cognition\u27s neural mechanisms and memory. It also explores Rasmussen\u27s S-R-K behaviors and Brain Network Theory’s (BNT) potential for measuring forgetting, cognition, and predicting training needs. The multidisciplinary approach of the study reinforces the importance of integrating insights from cognitive psychology, behavior analysis, and brain connectivity research. Research experiments were conducted at the University of North Dakota\u27s Integrated Lunar Mars Analog Habitat (ILMAH), gathering data from selected subjects via cognitive neuroscience tools and Electroencephalography (EEG) recordings to evaluate neurocognitive performance. The data analysis aimed to assess brain network activations during mentally demanding activities and compare EEG power spectra across various frequencies, latencies, and scalp locations. Despite facing certain challenges, including inadequacies of the current adapter boards leading to analysis failure, the study provides crucial lessons for future research endeavors. It highlights the need for swift adaptation, continual process refinement, and innovative solutions, like the redesign of adapter boards for high radio frequency noise environments, for the collection of high-quality EEG data. In conclusion, while the research did not reveal statistically significant differences between the experimental and control groups, it furnished valuable insights and underscored the need to optimize astronaut performance, well-being, and mission success. The study contributes to the ongoing evolution of training methodologies, with implications for future space exploration endeavors

The Future of Medicine: Frontiers in Integrative Health and Medicine

Contemporary healthcare trends indicate that many chronic and communicable diseases are related to lifestyle, stress, personal choices and systemic factors. In response to the shortfalls of modern medicine regarding the prevention of these diseases and the promotion of whole-person health, providers and consumers worldwide are exploring integrative, natural and complementary approaches to prevention, treatment and health promotion. These trends harbor the future of medicine. The issues of clinician burnout, high rates of adverse effects, high cost, and lack of rigorous methods to promote individual and collective immunity are addressed by leading physicians and scientists from around the world. The original research and reviews in this volume investigate efficacy, molecular mechanisms and hypotheses that suggest that traditional systems of medicine and health, e.g., Ayurveda, yoga, traditional Chinese medicine, and mind–body–lifestyle medicine, may offer preventive and cost-effective solutions to contemporary health care challenges. Integrating innovative health approaches with conventional medicine offers a whole system of medicine that encompasses the individual, family, community and environment—from single person to planetary health

Evaluation of different segmentation-based approaches for skin disorders from dermoscopic images

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2022-2023. Tutor/Director: Sala Llonch, Roser, Mata Miquel, Christian, Munuera, JosepSkin disorders are the most common type of cancer in the world and the incident has been lately increasing over the past decades. Even with the most complex and advanced technologies, current image acquisition systems do not permit a reliable identification of the skin lesion by visual examination due to the challenging structure of the malignancy. This promotes the need for the implementation of automatic skin lesion segmentation methods in order to assist in physicians’ diagnostic when determining the lesion's region and to serve as a preliminary step for the classification of the skin lesion. Accurate and precise segmentation is crucial for a rigorous screening and monitoring of the disease's progression. For the purpose of the commented concern, the present project aims to accomplish a state-of-the-art review about the most predominant conventional segmentation models for skin lesion segmentation, alongside with a market analysis examination. With the rise of automatic segmentation tools, a wide number of algorithms are currently being used, but many are the drawbacks when employing them for dermatological disorders due to the high-level presence of artefacts in the image acquired. In light of the above, three segmentation techniques have been selected for the completion of the work: level set method, an algorithm combining GrabCut and k-means methods and an intensity automatic algorithm developed by Hospital Sant Joan de Déu de Barcelona research group. In addition, a validation of their performance is conducted for a further implementation of them in clinical training. The proposals, together with the got outcomes, have been accomplished by means of a publicly available skin lesion image database